Mercurial > octave-nkf
view scripts/sparse/sprandn.m @ 13064:bae887ebea48
codesprint: Add input validation and tests for sprandsym.m
* sprandsym.m: Add input validation and tests for sprandsym.m.
* sprandn.m: Remove unnecessary output from find()
author | Rik <octave@nomad.inbox5.com> |
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date | Sat, 03 Sep 2011 11:29:24 -0700 |
parents | 14422cc782b2 |
children | 6db186dfdeaa |
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## Copyright (C) 2004-2011 Paul Kienzle ## ## This file is part of Octave. ## ## Octave is free software; you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or (at ## your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## ## Original version by Paul Kienzle distributed as free software in the ## public domain. ## -*- texinfo -*- ## @deftypefn {Function File} {} sprandn (@var{m}, @var{n}, @var{d}) ## @deftypefnx {Function File} {} sprandn (@var{s}) ## Generate a random sparse matrix. The size of the matrix will be ## @var{m} by @var{n}, with a density of values given by @var{d}. ## @var{d} should be between 0 and 1. Values will be normally ## distributed with mean of zero and variance 1. ## ## Note: sometimes the actual density may be a bit smaller than @var{d}. ## This is unlikely to happen for large really sparse matrices. ## ## If called with a single matrix argument, a random sparse matrix is ## generated wherever the matrix @var{S} is non-zero. ## @seealso{sprand} ## @end deftypefn ## Author: Paul Kienzle <pkienzle@users.sf.net> function S = sprandn (m, n, d) if (nargin != 1 && nargin != 3) print_usage (); endif if (nargin == 1) [i, j] = find (m); [nr, nc] = size (m); S = sparse (i, j, randn (size (i)), nr, nc); return; endif if (!(isscalar (m) && m == fix (m) && m > 0)) error ("sprand: M must be an integer greater than 0"); endif if (!(isscalar (n) && n == fix (n) && n > 0)) error ("sprand: N must be an integer greater than 0"); endif if (d < 0 || d > 1) error ("sprand: density D must be between 0 and 1"); endif mn = m*n; k = round (d*mn); idx = unique (fix (rand (min (k*1.01, k+10), 1) * mn)) + 1; ## idx contains random numbers in [1,mn] ## generate 1% or 10 more random values than necessary in order to ## reduce the probability that there are less than k distinct ## values; maybe a better strategy could be used but I don't think ## it's worth the price. ## actual number of entries in S k = min (length (idx), k); j = floor ((idx(1:k)-1)/m); i = idx(1:k) - j*m; if (isempty (i)) S = sparse (m, n); else S = sparse (i, j+1, randn (k, 1), m, n); endif endfunction ## FIXME: Test for density can't happen until code of sprandn is improved %!test %! s = sprandn (4, 10, 0.1); %! assert (size (s), [4, 10]); ##%! assert (nnz (s) / numel (s), 0.1, .01); %% Test 1-input calling form %!test %! s = sprandn (sparse ([1 2 3], [3 2 3], [2 2 2])); %! [i, j] = find (s); %! assert (sort (i), [1 2 3]'); %! assert (sort (j), [2 3 3]'); %% Test input validation %!error sprandn () %!error sprandn (1, 2) %!error sprandn (1, 2, 3, 4) %!error sprandn (ones(3), 3, 0.5) %!error sprandn (3.5, 3, 0.5) %!error sprandn (0, 3, 0.5) %!error sprandn (3, ones(3), 0.5) %!error sprandn (3, 3.5, 0.5) %!error sprandn (3, 0, 0.5) %!error sprandn (3, 3, -1) %!error sprandn (3, 3, 2)